State of the art hearing devices comprise a number of algorithms to deal with various specific tasks (typically related to different acoustic environments encountered by the hearing device/user, and/or to the particular needs of the user), e.g. noise reduction, directionality, level dependent compression, frequency dependent amplification, frequency compression, streamed audio reception, etc.
As both the number of algorithms and the complexity of these algorithms rise in a hearing device, the need for managing the use of the algorithms, e.g. for powering/scaling down algorithms (or only a part of algorithm) in order to save power and thus prolong the battery lifetime emerges.
US20140321682A1 describes various sensors for use in an automatic power down of a hearing instrument with a view to reducing power consumption when not in use (e.g. not worn be the user). A reduced draw on the battery increases the time between battery change (or between chargings, when rechargeable batteries are used), which increases user convenience.
However, algorithm(s) should only be powered/scaled down in time periods where this can be done without loss of performance. This calls for a Power Down Detector, which detects the time periods where an algorithm can be safely powered/scaled down.
One such algorithm relates to feedback control. Acoustic feedback from loudspeaker to microphone may be a problem in audio systems or devices (e.g. hearing devices). Adaptive feedback cancellation has the ability to track acoustic feedback path changes over time (in a feedback estimation unit). It is e.g. based on a linear time invariant filter to estimate the acoustic feedback path for which its filter weights are updated over time (i.e. an adaptive filter). The filter update may be calculated using stochastic gradient algorithms, e.g. including some form of the Least Mean Square (LMS) or the Normalized LMS (NLMS) algorithms. They both have the property to minimize the error signal in the mean square sense with the NLMS additionally normalizing the filter update with respect to the squared Euclidean norm of some reference signal.